Competencias docentes en la práctica de la computación

In the course of analyzing data for this study, the researcher employed both descriptive statistics method and quantitative statistical tools. The study adopted the frequency table, pie and bar charts and simple percentage statistical method in analyzing the demographic data and the research objectives responses on the various elements of job analysis, service quality, personnel utilization, attracting personnel and employee compensation in the study area. Pie and bar charts are blocks in which single bars are used to denote different

101

magnitudes or categories of variables and each in proportion to the frequency of each category. It is one of the common methods of presenting statistical data. Thus, pie and bar charts drawn from this analysis were used to interpret results of the questionnaire. Simple percentage was used as descriptive method. Simple percentage is a mathematical tool or approach for determining proportionality within a set of element. Simple percentage entails using the diverse response from respondents in categorizing them and thereby drawing the represented percentage for each of the group. The results of this study are discussed in chapter four.

Consequently, in order to test the research hypotheses and establish the relationship and the strength of the relationship between the variables under investigation, Pearson Product Moment Correlation Coefficient (PPMC) and Simple Regression Analysis techniques were used as quantitative statistical tools for this study. Pearson Product Moment Correlation Coefficient and Regression Analysis tests are inferential statistics.

While Pearson Product Moment Correlation Coefficient is used as a tool for establishing the relationship between two or more variables, Regression Analysis determines the extent to which dependent variable is explained by independent variables. Pearson Product Moment Correlation Coefficient (PPMC) was used to test hypotheses II and IV.

The statistical formula for the correlation coefficient is given below:

Σxy -ΣxΣy n

Σ= Σx² -(Σx)² (Σy²-(Σy)²

N n

102

Where:

n= the total no of observation

(Σx) =sum of independent variable (population) (Σy)=sum of the dependent variable

(Σxy) = sum of the product of

x

^and

y

(Σx²⁾ = sum of the squares of

xΣΣ

(Σx)²= square of the sum of

x

(Σy²⁾ = sum of the squares of

y

Hypothesis I and III on the other hand were addressed through the application of Simple Regression Analysis. The implicit specifications of the models used are:

Service Culture=

f

(Job Analysis)

---2

Employee Commitment =

f

(Job Analysis)

---3

Explicitly, models 2 and 3 becomes 4 and 5

Service Culture =

 + β

Job Analysis

+е --- 4

Employee Commitment =

 + β

Job Analysis

+ е

Whereas

 + β

are parameters to be estimated, while

е

is the error term designed to capture variables not included in the model.

Measurement of Research Variables

a. Job Analysis: Job analysis measure was measured with 6 questions items relating to Job analysis (items number 6, 7, 8, 9, 10, 11, 12, 13 and 14) were included in the questionnaire with a 5 point Likert scale of Disagree (1), Strongly Disagree (2), Not Sure (3), Agree (4), and Strongly Agree (5). The average scale of the responses of the

103

respondents represents the rating of job analysis which was used to assess the level of job analysis

b. Service Culture: To measure service culture 4 questionnaire items relating to service culture, (items numbers 15, 16, 17, 18, 19 and 20) were drafted in the questionnaire with a 5 point Likert scale of Disagree (1), Strongly Disagree (2), Not Sure (3), Agree (4), and Strongly Agree (5). The average scale of the responses of the respondents represents the rating of service culture which was used to assess the level of service culture.

c. Quality of Service Delivery: To measure quality of service, 4 questionnaire items relating to quality of service (items number 21, 22, 23, 24 and 25) were included in the questionnaire with a 5 point Likert scale of Disagree (1), Strongly Disagree (2), Not Sure (3), Agree (4), and Strongly Agree (5). The average scale of the responses of the respondents represents the rating of quality of service delivery which was used to assess the level of quality of service delivery.

d. Employee Commitment: To measure employee commitment, 3 questionnaire items relating to employee commitment (items number 26, 27, 28, 29, 30 and 31) were included in the questionnaire with a 5 point Likert scale of Disagree (1), Strongly Disagree (2), Not Sure (3), Agree (4), and Strongly Agree (5). The average scale of the responses of the respondents represents the rating of employee commitment which was used to assess the level of employee commitment.

e. Customer Experience: To measure customer experience, 3 questionnaire items relating to customer experience (items number 32, 33, 34, 35, 36 and 37) were included

104

in the questionnaire with a 5 point Likert scale of Disagree (1), Strongly Disagree (2), Not Sure (3), Agree (4), and Strongly Agree (5). The average scale of the responses of the respondents d the rating of customer experience which was used to assess the level of customer experience.

The results of the returned questionnaires were captured on Microsoft Excel and then exported to Statistical Packages for Social Science (SPSS) for analysis and interpretation.

The results were later used to draw deductions and conclusions on the subject matter of study in the concluding chapter.

105

CHAPTER FOUR

DATA PRESENTATION AND ANALYSIS

This chapter presents the data used in examining the effects of job analysis on service delivery in Federal Airports Authority of Nigeria (FAAN). It also presents analyses and interprets the data obtained through the administration of questionnaire to selected members of staff of Federal Airports Authority of Nigeria.

The researcher distributed a total of three hundred and eighty -six (386) questionnaires of thirty-seven (37) items each to members of staff of the Federal Airports Authority of Nigeria (FAAN). As a result of frequent persuasion on the importance of responding fully and honestly to the questionnaire, the researcher was able to achieve questionnaire return of three hundred and fifty-six (356) responses while thirty (30) were not returned out of the total distributed three hundred and eighty -six (386). Out of these numbers, twenty-two (22) copies of the questionnaire were not properly filled, leaving a total of three hundred and thirty-four (334) usable questionnaires yielding a response rate of 87percent.

The researcher proceeded with the analysis of the data as 87percent response rate is regarded as very satisfactory for this study. According to Babbie and Mouton (2001), some rules of thumb about the return/response rate is that a response rate of 50percent is adequate for analysis and reporting, 60percent is good while 70percent is very good.

In document Impactos y Perspectivas de la Capacitación en Computación de los Docentes de Educación Básica y Bachillerato del Instituto Superior de Música Vicente Anda Aguirre y Jardín de Infantes Primer Año de Educación Básica “General Lavalle” de la Ciudad de Riobam (página 34-39)